Title :

STRONG: metagenomics strain resolution on assembly graphs

Author(s) :

Limasset, Antoine [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Quince, Christopher [Auteur]
Nurk, Sergey [Auteur]
Raguideau, Sebastien [Auteur]
James, Robert [Auteur]
Soyer, Orkun [Auteur]
Summers, J. Kimberly [Auteur]
Eren, A. Murat [Auteur]
Chikhi, Rayan [Auteur]
Darling, Aaron [Auteur]

Journal title :

Genome Biology

Publisher :

BioMed Central

Publication date :

2021-06-29

ISSN :

1465-6906

HAL domain(s) :

Informatique [cs]/Bio-informatique [q-bio.QM]

English abstract : [en]

Abstract We introduce STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, from multiple metagenome samples. STRONG performs coassembly, and binning into metagenome assembled genomes (MAGs), and ...
Show more >Abstract We introduce STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, from multiple metagenome samples. STRONG performs coassembly, and binning into metagenome assembled genomes (MAGs), and stores the coassembly graph prior to variant simplification. This enables the subgraphs and their unitig per-sample coverages, for individual single-copy core genes (SCGs) in each MAG, to be extracted. A Bayesian algorithm, BayesPaths, determines the number of strains present, their haplotypes or sequences on the SCGs, and abundances. STRONG is validated using synthetic communities and for a real anaerobic digestor time series generates haplotypes that match those observed from long Nanopore reads.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL